Distant metastasis is one of the main reasons for the failure of nasopharyngeal carcinoma (NPC) treatment, and descending type of nasopharyngeal carcinoma (type D NPC) is more prone to distant metastasis. Few people have explored the relationship between the radiomics characteristics of lymph nodes and the distant metastasis of type D NPC. Therefore, we establish a nomogram based on radiomics risk factors to predict distant metastasis in patients with type D NPC. This study retrospectively included 144 type D NPC (T1-2N2-3MO, AJCC 8th). 2600 features were extracted each from CT and MRI examinations conducted before treatment, respectively. Feature selection was performed by least absolute shrinkage and selection operator regression. A binary logistic regression model was used to construct a nomogram, and the C-index and calibration curve were used to evaluate the discrimination and accuracy of the nomogram. Combining CT and MRI radiomics features with a multimodal radiomics model, the average area under curve of the synthetic minority oversampling technique (SMOTE) data set was 0.873 (95% confidence interval [CI]: 0.797-0.949). The C-index in the training and validation sets of the original data set were 0.91 (95% CI: 0.848-0.972) and 0.815 (95% CI: 0.664-0.967); the sensitivity were 0.75 and 0.545, the specificity were 0.932 and 0.903, and the accuracy were 0.882 and 0.81. Therefore, we concluded that the multimodal radiomics model in predicting distant metastasis in descending type of NPC patients was good. The proposed model can provide a reference for precise treatment and prognosis prediction.